Stepping back: Direct marketing guru and Internet junkie, Gregory Ng, introduced me to twitter. After a couple of days of use, I got the general gist of it, but I really wanted to figure out what I could learn from it. After all, this was really close to my dream of being able to work all day mining AIM or MSN conversations and then return home with my 6 friends to our dark haired princess who washes our clothes and makes us supper. I just want to learn how to serve you better. I promise I am only quasi-evil!

So I built a little MySQL database and PERL script that started storing tweets from people that I felt were influential on twitter. People like Paul Kedrosky and Chris Brogan. I soon discovered that this was the wrong approach. While it’s interesting and helpful to get the opinions and most commonly used word pairs of the experts, it is the twitter population at large that can help you tell a story about what is happening in twitterland. You can use one of the many cool search tools like Summize to get a buzz

pulse, or you can use some of the cool first generation analytics apps, some of which I mention below.

The Twalaxy’s Attempts at Buzz Measurement

• Twitterverse

  is a twitter tag cloud that shows what is happening within the last 1 to 10 hours on twitter. You can set it up to look at one word or two word phrases.

• Intwition

  is a cool tool that tells you the most popular links on twitter for the day. It also tries to suggest what will be popular dude to its hotness within the last 8 hours, and it also gives a 5 day summary.

• TwitterBuzz and even better: Twitturly

  Twitterbuzz is a link aggregator. It shows the most popular links on twitter. It aggregates the primary URLs and then allows you to drill down. The only problem with this is that it aggregates tinyurl, dwarfurl, snurl etc instead of following them to the actual link which would be far more interesting. It also is not setup to capture and display double-byte characters so Chinese tweets are not legible. <a href=”http://twitter.com/waynesutton/statuses/808211269″>@waynesutton just turned me on to Twitturly </a> which I think is even more compelling because it DOES follow the links and has a really slick look and feel.

Twitterverse 2.0

These apps are cute like and they do give us a flavor for what is happening, but what happens if we do more than make a cute app for the sake of saying we did have a cute twitter app? How about some natural language processing to tell us if the message is positive or negative. How about we apply that to a brand? Consider a new competitive product release like the (fictional) Dunkin Donuts Strawberry Cheesecake Latte and (you know you want it) Starshmuck’s Raspberry Ripple Espresso. How about a compete.com-esque tool that allows me to enter the products and gives me a trend line showing the positive or negative buzz about the products?

Even better would be an aggregation of these, similar to what is happening on Trendrr but using natural language processing to care for abbreviations, related works and the like. Trendrr is a great first step and I think could prove to be a bridge to the Twitterverse 2.0.

I will be keeping my bananas peeled on these developments. Tweet me with or comment with others! @schneidermike.

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